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The 2007–2008 economic crash has had long-lasting effects on Greece’s biomedical research landscape. It has exposed a gap in support for countries that are classified as high income but are living under austerity measures. A new model is needed for optimal utilization of the intellectual and natural resources that such countries can offer to improve the global research landscape.
In just a few weeks’ time, leaders across the globe will have to start making decisions about lifting lockdown policies, with considerable social, economic and political consequences. We propose a framework for what is arguably the most difficult health challenge that governments have faced since the beginning of this century: a responsible lockdown exit strategy.
Vannevar Bush enshrined the ‘basic’ and ‘applied’ research dichotomy on which much of science policy is still built 75 years later. However, it is time to assess whether this vision for science best serves the purposes of medical research and physician-scientists in the 21st century.
Previous crises have shown how an economic crash has dire consequences for public health. But in the COVID-19 pandemic, the world is entering uncharted territory. The world’s leaders must prepare to preserve health.
In the COVID-19 pandemic, the most vulnerable people are most likely to be the hardest hit. What can we learn from past epidemics to protect not only refugees but also the wider population?
Large-scale collection of data could help curb the COVID-19 pandemic, but it should not neglect privacy and public trust. Best practices should be identified to maintain responsible data-collection and data-processing standards at a global scale.
COVID-19 has affected vulnerable populations disproportionately across China and the world. Solid social and scientific evidence to tackle health inequity in the current COVID-19 pandemic is in urgent need.
Private industry is increasingly soliciting hospitals to sell or share health data and biospecimens, but current laws offer more disclosure and consent protections for research participants than for patients receiving clinical care. Hospitals can offer more protections than required by law, however, and should move toward greater transparency with their patients about the research use of clinical health data and biospecimens to respect patients and avoid distrust.
The World Health Organization’s targets for eliminating hepatitis C virus by 2030 have been deemed ambitious by many. However, we believe they are achievable, provided they are supported by global commitment.
In an increasingly hyper-polarized world, the weight of public perception can dissuade policymakers from implementing scientifically sound health policies. The scientific community has a responsibility to make facts outweigh opinion.
An Ebola virus outbreak taking place in the complex political and social context of The Democratic Republic of the Congo has forced the research community to reflect on their approach to community engagement. Katharine Wright and Michael Parker, on behalf of the Nuffield Council on Bioethics Working Group on research in global health emergencies, say that those affected need to influence research choices from the very beginning and that the value of their knowledge must be recognized.
The strengthening of the Chinese Center for Disease Control and Prevention has been a turning point in outbreak responses in the area. This represents very welcome progress and development for global health security and diplomacy.
Although examples of algorithms designed to improve healthcare delivery abound, for many, clinical integration will not be achieved. The deployment cost of machine learning models is an underappreciated barrier to success. Experts propose three criteria that, assessed early, could help estimate the deployment cost.
Among the many promises of big data, one of the most exciting could be the potential to unlock the detection of cancer before advanced malignancy ensures, which means opening up a whole new understanding of the disease.
Healthcare is an imperfect practice, with disparities in care reflecting those in society. While algorithms may be misued to amplify biases, they may also be used to identify and correct disparities.
